{"id":"W2494099403","doi":"10.1145/2851613.2851643","title":"PatchWork, a scalable density-grid clustering algorithm","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Computer Research Institute of Montréal","funders":"","keywords":"Cluster analysis; Computer science; Scalability; SPARK (programming language); CURE data clustering algorithm; Data mining; Canopy clustering algorithm; Correlation clustering; Computation; Knowledge extraction; Data stream clustering; Anomaly detection; Outlier; Algorithm; Artificial intelligence; Database","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003504802,0.0001866326,0.0001963419,0.0001397482,0.0001634407,0.0001796394,0.001225068,0.00007324203,0.00009338309],"category_scores_gemma":[0.00007932079,0.0001232068,0.00006777726,0.0004679884,0.00007710839,0.0009530478,0.001535027,0.0001402463,0.0008275414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001528478,"about_ca_system_score_gemma":0.00006504205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004835158,"about_ca_topic_score_gemma":0.00002060784,"domain_scores_codex":[0.9978146,0.00006820112,0.0002366968,0.0006270064,0.0005208831,0.000732618],"domain_scores_gemma":[0.9983708,0.0002142883,0.0000490095,0.0009603523,0.0001552582,0.0002502803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003432959,0.00003455135,0.00009988416,0.000006718873,0.00001148245,0.00007170814,0.00005651294,0.00005730964,0.002991818,0.000773987,0.001002077,0.9948905],"study_design_scores_gemma":[0.00199329,0.0003527821,0.001286781,0.0002139371,0.000005166102,0.0003753646,0.00004379513,0.8990744,0.04860976,0.00889432,0.0380918,0.001058546],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009144592,0.00003394351,0.9928827,0.001845322,0.0005677522,0.0001491068,0.000002435501,0.00056763,0.003036627],"genre_scores_gemma":[0.02459631,0.00005369349,0.9580076,0.0002817111,0.0003082987,0.00003456052,5.904752e-7,0.00002867729,0.01668859],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.993832,"threshold_uncertainty_score":0.9999504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01705739088045538,"score_gpt":0.2673199606908087,"score_spread":0.2502625698103533,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}